Radium isotopes as a tracer of sediment‐water column exchange in the North Sea
Bibliographic record
Abstract
Abstract Sediment‐water column exchange plays an important role in coastal biogeochemistry. We utilize short‐lived radium isotopes (224Ra and 223Ra) to understand and quantify the dominant processes governing sediment‐water column exchange throughout the North Sea. Our comprehensive survey, conducted in September 2011, represents the first of its kind conducted in the North Sea. We find that two main sources regulate surface Ra distributions: minor coastal input from rivers and shallow mudflats and North Sea sediments as the dominant source. Pore waters show 100‐fold larger activities than the water column. North Sea sediment characteristics such as porosity and mean grain size, as well as turbulence at the sediment‐water interface, are the dominant factors contributing to variability of Ra efflux. Ra inventory and mass balance approaches consistently yield high benthic Ra effluxes in the southern North Sea, driven by strong tidal and wind mixing, which in turn cause high sediment irrigation rates. These results exceed incubation‐based Ra flux estimates and the majority of previously reported Ra flux estimates for other regions. Ra‐based estimates of benthic alkalinity fluxes compare well to observed values, and the high rates of Ra efflux imply a potentially significant exchange of other products of sedimentary reactions, including carbon and nutrient species. Passive tracer simulations lend strong support to the Ra source attribution and imply seasonal variation in the surface water Ra distribution depending on stratification conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".